Análise Completa dos Dados Neurocognitivos

library(tibble)
library(readxl)
library(dplyr)
library(gtExtras)
library(ggplot2)
library(plotly)
library(viridis)
library(hrbrthemes)
library(openxlsx)


#data <- readxl::read_xlsx ("BPAs_FDTs_ RAVLTs_EscoreZ.xlsx", sheet = 1)


#install.packages("tibble")
#install.packages("openxlsx")




#setwd("C:/Users/User/Desktop/Analysis in R/NeuroCovid")

getwd()

[1] "C:/Users/felip/Desktop/R/4_analise_"

data <- readxl::read_xlsx ("DADOS_BRUTOS_COVID_LONGA_PREENCHENDO.xlsx")

data <- na.omit(data)

 
################################## BPA Z-Score Calculating  #####################################

                                # 1º Try
                  # TENTATIVA DE CRIAÇÃO DE FUNÇÃO

cbind(data)

calcular_z_score <- function(x, media, desvio_padrao) {
  if (x >= 21 & x <= 30) {
    z_score <- (x - media) / desvio_padrao
    return(z_score)
  }
}

                                # 2º Try

# Definir os valores constantes de média e desvio padrão para cada faixa etária
constantes <- tribble(
  ~LIMIT_AGE, ~media_constante, ~desvio_padrao_constante,
  "18-20", 85.79, 22.53,
  "21-30", 87.08, 21.50,
  "31-40", 85.48, 22.56,
  "41-49", 80.72, 22.85
)

                                # 3º Try
  # COMEÇAR DAQUI ----->  DETERMINANDO LIMITES A SEREM APLICADOS

limites_idade <- c(18, 20, 30, 40, 50)


data <- data %>%
  mutate(LIMIT_AGE = cut(AGE, breaks = limites_idade, labels =
                           c("18-20", "21-30", "31-40", "41-50"))) %>% 
  arrange(AGE)
  
data

# Calcular o Z-score usando as constantes para cada faixa etária


#BPA_CONC

BPA_CONC_EscoreZ <- data %>%
  mutate(BPA_CONC_EscoreZ = case_when(
    LIMIT_AGE == "18-20" ~ (BPA_CONC_POINTS - 85.79) / 22.53,
    LIMIT_AGE == "21-30" ~ (BPA_CONC_POINTS - 87.08) / 21.50,
    LIMIT_AGE == "31-40" ~ (BPA_CONC_POINTS - 85.48) / 22.56,
    LIMIT_AGE == "41-50" ~ (BPA_CONC_POINTS - 80.72) / 22.85,
    TRUE ~ NA_real_  # Caso padrão para outras faixas etárias
  )) %>%
  select(ID, AGE,GROUP,EDU_LEVEL, LIMIT_AGE,BPA_CONC_POINTS, BPA_CONC_EscoreZ) %>% 
  arrange(ID)

BPA_CONC_EscoreZ

#BPA_DIVD

BPA_DIVID_EscoreZ <- data %>%
  mutate(BPA_DIVID_EscoreZ = case_when(
    LIMIT_AGE == "18-20" ~ (BPA_DIVID_POINTS - 79.42) / 23.49,
    LIMIT_AGE == "21-30" ~ (BPA_DIVID_POINTS - 77.19) / 24.42,
    LIMIT_AGE == "31-40" ~ (BPA_DIVID_POINTS - 71.28) / 25.33,
    LIMIT_AGE == "41-50" ~ (BPA_DIVID_POINTS - 61.22) / 26.53,
    TRUE ~ NA_real_  # Caso padrão para outras faixas etárias
  )) %>%
  select(ID,BPA_DIVID_POINTS, BPA_DIVID_EscoreZ) %>% 
  arrange(ID)

BPA_DIVID_EscoreZ

#BPA_ALTERN

BPA_ALTERN_EscoreZ <- data %>%
  mutate(BPA_ALTERN_EscoreZ = case_when(
    LIMIT_AGE == "18-20" ~ (BPA_ALTERN_POINTS - 93.21) / 21.76,
    LIMIT_AGE == "21-30" ~ (BPA_ALTERN_POINTS - 87.53) / 23.56,
    LIMIT_AGE == "31-40" ~ (BPA_ALTERN_POINTS - 82.28) / 24.84,
    LIMIT_AGE == "41-50" ~ (BPA_ALTERN_POINTS - 72.70) / 25.80,
    TRUE ~ NA_real_  # Caso padrão para outras faixas etárias
  )) %>%
  select(ID,BPA_ALTERN_POINTS, BPA_ALTERN_EscoreZ) %>% 
  arrange(ID)

BPA_ALTERN_EscoreZ 

#BPA_TOTAL

BPA_TOTAL_EscoreZ <- data %>%
  mutate(BPA_TOTAL_EscoreZ = case_when(
    LIMIT_AGE == "18-20" ~ (BPA_TOTAL - 258.42) / 56.59,
    LIMIT_AGE == "21-30" ~ (BPA_TOTAL - 251.79) / 58.61,
    LIMIT_AGE == "31-40" ~ (BPA_TOTAL - 239.04) / 62.77,
    LIMIT_AGE == "41-50" ~ (BPA_TOTAL - 214.65) / 64.33,
    TRUE ~ NA_real_  # Caso padrão para outras faixas etárias
  )) %>%
  select(ID,BPA_TOTAL, BPA_TOTAL_EscoreZ) %>% 
  arrange(ID)

BPA_TOTAL_EscoreZ

BPAs_EscoreZ <- bind_cols(BPA_CONC_EscoreZ, BPA_DIVID_EscoreZ, BPA_ALTERN_EscoreZ, BPA_TOTAL_EscoreZ) %>% 
          na.omit()

New names:
• `ID` -> `ID...1`
• `ID` -> `ID...8`
• `ID` -> `ID...11`
• `ID` -> `ID...14`

write.xlsx(BPAs_EscoreZ, file = "BPAs_EscoreZ.xlsx")




################################## FDT Z-Score Calculating  #####################################


data <- readxl::read_xlsx ("DADOS_BRUTOS_COVID_LONGA_PREENCHENDO.xlsx")

data <- na.omit(data)

                # DETERMINANDO LIMITES A SEREM APLICADOS

limites_idade <- c(18, 19, 34, 50)

                # ADICIONANDO COLUNA AO DADO, RELACIONADO AOS LIMITES DESEJADOS

data <- data %>%
  mutate(LIMIT_AGE = cut(AGE, breaks = limites_idade, labels =
                           c("18", "19-34", "35-50"))) %>% 
  arrange(AGE)
  
data

#FDT READING

FDT_READING_TIME_Z <- data %>%
  mutate(FDT_READING_TIME_Z = case_when(
    LIMIT_AGE == "18" ~ (FDT_READING_TIME - 20.4) / 4.1,
    LIMIT_AGE == "19-34" ~ (FDT_READING_TIME - 22) / 5.6,
    LIMIT_AGE == "35-50" ~ (FDT_READING_TIME - 23.9) / 6.5,
    TRUE ~ NA_real_  # Caso padrão para outras faixas etárias
  )) %>%
  select(ID,AGE, EDU_LEVEL,GROUP, LIMIT_AGE,FDT_READING_TIME,  FDT_READING_TIME_Z) %>% 
  arrange(ID)


FDT_READING_TIME_Z

#FDT COUTING

FDT_COUNTING_TIME_Z <- data %>%
  mutate(FDT_COUNTING_TIME_Z = case_when(
    LIMIT_AGE == "18" ~ (FDT_COUNTING_TIME - 23.8) / 3.5,
    LIMIT_AGE == "19-34" ~ (FDT_COUNTING_TIME - 24.2) / 5.2,
    LIMIT_AGE == "35-50" ~ (FDT_COUNTING_TIME - 27.1) / 7.2,
    TRUE ~ NA_real_  # Caso padrão para outras faixas etárias
  )) %>%
  select(ID,FDT_COUNTING_TIME, FDT_COUNTING_TIME_Z) %>% 
  arrange(ID)


FDT_COUNTING_TIME_Z

#FDT CHOOSING

FDT_CHOOSING_TIME_Z <- data %>%
  mutate(FDT_CHOOSING_TIME_Z = case_when(
    LIMIT_AGE == "18" ~ (FDT_CHOOSING_TIME - 34) / 5.9,
    LIMIT_AGE == "19-34" ~ (FDT_CHOOSING_TIME - 36.9) / 10,
    LIMIT_AGE == "35-50" ~ (FDT_CHOOSING_TIME - 41.7) / 14.5,
    TRUE ~ NA_real_  # Caso padrão para outras faixas etárias
  )) %>%
  select(ID,FDT_CHOOSING_TIME, FDT_CHOOSING_TIME_Z) %>% 
  arrange(ID)


FDT_CHOOSING_TIME_Z

#FDT CHANGING

FDT_CHANGING_TIME_Z <- data %>%
  mutate(FDT_CHANGING_TIME_Z = case_when(
    LIMIT_AGE == "18" ~ (FDT_CHANGING_TIME - 44.8) / 9.1,
    LIMIT_AGE == "19-34" ~ (FDT_CHANGING_TIME - 46) / 13,
    LIMIT_AGE == "35-50" ~ (FDT_CHANGING_TIME - 53.6) / 18.4,
    TRUE ~ NA_real_  # Caso padrão para outras faixas etárias
  )) %>%
  select(ID,FDT_CHANGING_TIME, FDT_CHANGING_TIME_Z) %>% 
  arrange(ID)


FDT_CHANGING_TIME_Z

#FDT INHIBITION

FDT_INHIBITION_Z <- data %>%
  mutate(FDT_INHIBITION_Z = case_when(
    LIMIT_AGE == "18" ~ (FDT_INHIBITION - 13.6) / 4.9,
    LIMIT_AGE == "19-34" ~ (FDT_INHIBITION - 14.8) / 8.3,
    LIMIT_AGE == "35-50" ~ (FDT_INHIBITION - 17.8) / 12,
    TRUE ~ NA_real_  # Caso padrão para outras faixas etárias
  )) %>%
  select(ID,FDT_INHIBITION, FDT_INHIBITION_Z) %>% 
  arrange(ID)


FDT_INHIBITION_Z

#FDT FLEXBILITY

FDT_FLEXIBILITY_Z <- data %>%
  mutate(FDT_FLEXIBILITY_Z = case_when(
    LIMIT_AGE == "18" ~ (FDT_FLEXIBILITY - 24.4) / 7.8,
    LIMIT_AGE == "19-34" ~ (FDT_FLEXIBILITY - 23.9) / 10.8,
    LIMIT_AGE == "35-50" ~ (FDT_FLEXIBILITY - 29.7) / 15.7,
    TRUE ~ NA_real_  # Caso padrão para outras faixas etárias
  )) %>%
  select(ID,FDT_FLEXIBILITY, FDT_FLEXIBILITY_Z) %>% 
  arrange(ID)


FDT_FLEXIBILITY_Z

#BIND COLS E SALVAR

FDT_EscoreZ <- bind_cols(FDT_READING_TIME_Z,FDT_COUNTING_TIME_Z,FDT_CHOOSING_TIME_Z,
                         FDT_CHANGING_TIME_Z,FDT_INHIBITION_Z,FDT_FLEXIBILITY_Z)

New names:
• `ID` -> `ID...1`
• `ID` -> `ID...8`
• `ID` -> `ID...11`
• `ID` -> `ID...14`
• `ID` -> `ID...17`
• `ID` -> `ID...20`

write.xlsx(FDT_EscoreZ, file = "FDT_EscoreZ.xlsx")



################################## RAVLTS Z-Score Calculating #####################################

data <- readxl::read_xlsx ("DADOS_BRUTOS_COVID_LONGA_PREENCHENDO.xlsx")

data <- na.omit(data)



limites_idade <- c(18, 20, 30, 40, 50)


data <- data %>%
  mutate(LIMIT_AGE = 
           cut(AGE, breaks = limites_idade, labels = 
                 c("18-20", "21-30", "31-40", "41-50"))) %>% 
  arrange(AGE) 
  
data

#RAVLT A1

RAVLT_A1_Z <- data %>%
  mutate(RAVLT_A1_Z = case_when(
    LIMIT_AGE == "18-20" ~ (RAVLT_A1 - 6.8) / 1.7,
    LIMIT_AGE == "21-30" ~ (RAVLT_A1 - 6.5) / 1.7,
    LIMIT_AGE == "31-40" ~ (RAVLT_A1 - 6.1) / 1.6,
    LIMIT_AGE == "41-50" ~ (RAVLT_A1 - 6) / 1.6,

    TRUE ~ NA_real_  # Caso padrão para outras faixas etárias
  )) %>%
  select(ID, AGE,EDU_LEVEL,GROUP, LIMIT_AGE,RAVLT_A1,  RAVLT_A1_Z) %>% 
  arrange(ID)


RAVLT_A1_Z 

#RAVLT A2

RAVLT_A2_Z <- data %>%
  mutate(RAVLT_A2_Z = case_when(
    LIMIT_AGE == "18-20" ~ (RAVLT_A2 - 9.5) / 2.2,
    LIMIT_AGE == "21-30" ~ (RAVLT_A2 - 8.9) / 2.2,
    LIMIT_AGE == "31-40" ~ (RAVLT_A2 - 8.7) / 2,
    LIMIT_AGE == "41-50" ~ (RAVLT_A2 - 8.5) / 2,

    TRUE ~ NA_real_  # Caso padrão para outras faixas etárias
  )) %>%
  select(ID,RAVLT_A2, RAVLT_A2_Z) %>% 
  arrange(ID)


RAVLT_A2_Z

#RAVLT A3

RAVLT_A3_Z <- data %>%
  mutate(RAVLT_A3_Z = case_when(
    LIMIT_AGE == "18-20" ~ (RAVLT_A3 - 11) / 2.2,
    LIMIT_AGE == "21-30" ~ (RAVLT_A3 - 10.4) / 2.4,
    LIMIT_AGE == "31-40" ~ (RAVLT_A3 - 10.3) / 2.1,
    LIMIT_AGE == "41-50" ~ (RAVLT_A3 - 9.8) / 2.5,

    TRUE ~ NA_real_  # Caso padrão para outras faixas etárias
  )) %>%
  select(ID,RAVLT_A3, RAVLT_A3_Z) %>% 
  arrange(ID)


RAVLT_A3_Z

#RAVLT A4

RAVLT_A4_Z <- data %>%
  mutate(RAVLT_A4_Z = case_when(
    LIMIT_AGE == "18-20" ~ (RAVLT_A4 - 11.8) / 2.4,
    LIMIT_AGE == "21-30" ~ (RAVLT_A4 - 11.4) / 2.4,
    LIMIT_AGE == "31-40" ~ (RAVLT_A4 - 11.4) / 2.1,
    LIMIT_AGE == "41-50" ~ (RAVLT_A4 - 10.7) / 2.7,

    TRUE ~ NA_real_  # Caso padrão para outras faixas etárias
  )) %>%
  select(ID,RAVLT_A4,RAVLT_A4_Z) %>% 
  arrange(ID)


RAVLT_A4_Z

#RAVLT A5

RAVLT_A5_Z <- data %>%
  mutate(RAVLT_A5_Z = case_when(
    LIMIT_AGE == "18-20" ~ (RAVLT_A5 - 12.2) / 2.4,
    LIMIT_AGE == "21-30" ~ (RAVLT_A5 - 12.2) / 2.2,
    LIMIT_AGE == "31-40" ~ (RAVLT_A5 - 12.2) / 2.2,
    LIMIT_AGE == "41-50" ~ (RAVLT_A5 - 11.7) / 2.6,

    TRUE ~ NA_real_  # Caso padrão para outras faixas etárias
  )) %>%
  select(ID,RAVLT_A5, RAVLT_A5_Z) %>% 
  arrange(ID)


RAVLT_A5_Z

#RAVLT  B1

RAVLT_B1_Z <- data %>%
  mutate(RAVLT_B1_Z = case_when(
    LIMIT_AGE == "18-20" ~ (RAVLT_B1 - 6.3) / 1.8,
    LIMIT_AGE == "21-30" ~ (RAVLT_B1 - 5.7) / 1.8,
    LIMIT_AGE == "31-40" ~ (RAVLT_B1 - 5.3) / 1.6,
    LIMIT_AGE == "41-50" ~ (RAVLT_B1 - 4.9) / 1.6,

    TRUE ~ NA_real_  # Caso padrão para outras faixas etárias
  )) %>%
  select(ID,RAVLT_B1, RAVLT_B1_Z) %>% 
  arrange(ID)


RAVLT_B1_Z

#RAVLT A6

RAVLT_A6_Z <- data %>%
  mutate(RAVLT_A6_Z = case_when(
    LIMIT_AGE == "18-20" ~ (RAVLT_A6 - 11.1) / 2.5,
    LIMIT_AGE == "21-30" ~ (RAVLT_A6 - 10.9) / 2.6,
    LIMIT_AGE == "31-40" ~ (RAVLT_A6 - 10.8) / 2.4,
    LIMIT_AGE == "41-50" ~ (RAVLT_A6 - 9.8) / 2.8,

    TRUE ~ NA_real_  # Caso padrão para outras faixas etárias
  )) %>%
  select(ID,RAVLT_A6, RAVLT_A6_Z) %>% 
  arrange(ID)


RAVLT_A6_Z

#RAVLT A7

RAVLT_A7_Z <- data %>%
  mutate(RAVLT_A7_Z = case_when(
    LIMIT_AGE == "18-20" ~ (RAVLT_A7 - 11) / 2.7,
    LIMIT_AGE == "21-30" ~ (RAVLT_A7 - 10.7) / 2.7,
    LIMIT_AGE == "31-40" ~ (RAVLT_A7 - 10.3) / 2.4,
    LIMIT_AGE == "41-50" ~ (RAVLT_A7 - 9.6) / 2.8,

    TRUE ~ NA_real_  # Caso padrão para outras faixas etárias
  )) %>%
  select(ID,RAVLT_A7,RAVLT_A7_Z) %>% 
  arrange(ID)


RAVLT_A7_Z

#RAVLT REC

RAVLT_REC_Z <- data %>%
  mutate(RAVLT_REC_Z = case_when(
    LIMIT_AGE == "18-20" ~ (RAVLT_REC - 10) / 5.7,
    LIMIT_AGE == "21-30" ~ (RAVLT_REC - 11.4) / 4.7,
    LIMIT_AGE == "31-40" ~ (RAVLT_REC - 11.1) / 4.7,
    LIMIT_AGE == "41-50" ~ (RAVLT_REC - 9.9) / 5.6,

    TRUE ~ NA_real_  # Caso padrão para outras faixas etárias
  )) %>%
  select(ID,RAVLT_REC,RAVLT_REC_Z) %>% 
  arrange(ID)


RAVLT_REC_Z

#RAVLT_TOTALSCORE


RAVLT_TOTALSCORE_Z <- data %>%
  mutate(RAVLT_TOTALSCORE_Z = case_when(
    LIMIT_AGE == "18-20" ~ (RAVLT_TOTALSCORE - 51.4) / 8.7,
    LIMIT_AGE == "21-30" ~ (RAVLT_TOTALSCORE - 49.3) / 8.6,
    LIMIT_AGE == "31-40" ~ (RAVLT_TOTALSCORE - 48.6) / 8,
    LIMIT_AGE == "41-50" ~ (RAVLT_TOTALSCORE - 46.7) / 9.6,

    TRUE ~ NA_real_  # Caso padrão para outras faixas etárias
  )) %>%
  select(ID,RAVLT_TOTALSCORE, RAVLT_TOTALSCORE_Z) %>% 
  arrange(ID)

RAVLT_TOTALSCORE_Z

#RAVLT_ALT

RAVLT_ALT_Z <- data %>%
  mutate(RAVLT_ALT_Z = case_when(
    LIMIT_AGE == "18-20" ~ (RAVLT_ALT - 17.3) / 7.3,
    LIMIT_AGE == "21-30" ~ (RAVLT_ALT - 16.8) / 6.5,
    LIMIT_AGE == "31-40" ~ (RAVLT_ALT - 17.9) / 7,
    LIMIT_AGE == "41-50" ~ (RAVLT_ALT - 16.5) / 7.3,

    TRUE ~ NA_real_  # Caso padrão para outras faixas etárias
  )) %>%
  select(ID,RAVLT_ALT, RAVLT_ALT_Z) %>% 
  arrange(ID)




RAVLT_ALT_Z

#RAVLT_RETENTION

RAVLT_RETENTION_Z <- data %>%
  mutate(RAVLT_RETENTION_Z = case_when(
    LIMIT_AGE == "18-20" ~ (RAVLT_RETENTION - 1) / 0.2,
    LIMIT_AGE == "21-30" ~ (RAVLT_RETENTION - 1) / 0.27,
    LIMIT_AGE == "31-40" ~ (RAVLT_RETENTION - 0.97) / 0.19,
    LIMIT_AGE == "41-50" ~ (RAVLT_RETENTION - 1.01) / 0.34,

    TRUE ~ NA_real_  # Caso padrão para outras faixas etárias
  )) %>%
  select(ID,RAVLT_RETENTION, RAVLT_RETENTION_Z) %>% 
  arrange(ID)


RAVLT_RETENTION_Z

#RAVLT_PROAT_INTERFERENCE

RAVLT_PROAT_INTERFERENCE_Z <- data %>%
  mutate(RAVLT_PROAT_INTERFERENCE_Z = case_when(
    LIMIT_AGE == "18-20" ~ (RAVLT_PROAT_INTERFERENCE - 0.96) / 0.33,
    LIMIT_AGE == "21-30" ~ (RAVLT_PROAT_INTERFERENCE - 0.92) / 0.37,
    LIMIT_AGE == "31-40" ~ (RAVLT_PROAT_INTERFERENCE - 0.91) / 0.33,
    LIMIT_AGE == "41-50" ~ (RAVLT_PROAT_INTERFERENCE - 0.86) / 0.31,

    TRUE ~ NA_real_  # Caso padrão para outras faixas etárias
  )) %>%
  select(ID,RAVLT_PROAT_INTERFERENCE, RAVLT_PROAT_INTERFERENCE_Z) %>% 
  arrange(ID)


RAVLT_PROAT_INTERFERENCE_Z

#RAVLT_RETRO_INTERFERENCE

RAVLT_RETRO_INTERFERENCE_Z <- data %>%
  mutate(RAVLT_RETRO_INTERFERENCE_Z = case_when(
    LIMIT_AGE == "18-20" ~ (RAVLT_RETRO_INTERFERENCE - 0.96) / 0.68,
    LIMIT_AGE == "21-30" ~ (RAVLT_RETRO_INTERFERENCE - 0.89) / 0.17,
    LIMIT_AGE == "31-40" ~ (RAVLT_RETRO_INTERFERENCE - 0.94) / 0.74,
    LIMIT_AGE == "41-50" ~ (RAVLT_RETRO_INTERFERENCE - 0.84) / 0.18,

    TRUE ~ NA_real_  # Caso padrão para outras faixas etárias
  )) %>%
  select(ID,RAVLT_RETRO_INTERFERENCE, RAVLT_RETRO_INTERFERENCE_Z) %>% 
  arrange(ID)


RAVLT_RETRO_INTERFERENCE_Z

#BIND COLS E SALVAR

RAVLTs_EscoreZ <- bind_cols(RAVLT_A1_Z, RAVLT_A2_Z, RAVLT_A3_Z, RAVLT_A4_Z, RAVLT_A5_Z,
                            RAVLT_B1_Z, RAVLT_A6_Z, RAVLT_A7_Z, RAVLT_REC_Z, RAVLT_TOTALSCORE_Z,
                           RAVLT_RETENTION_Z, RAVLT_PROAT_INTERFERENCE_Z, RAVLT_RETRO_INTERFERENCE_Z ) 

New names:
• `ID` -> `ID...1`
• `ID` -> `ID...8`
• `ID` -> `ID...11`
• `ID` -> `ID...14`
• `ID` -> `ID...17`
• `ID` -> `ID...20`
• `ID` -> `ID...23`
• `ID` -> `ID...26`
• `ID` -> `ID...29`
• `ID` -> `ID...32`
• `ID` -> `ID...35`
• `ID` -> `ID...38`
• `ID` -> `ID...41`

write.xlsx(RAVLTs_EscoreZ, file = "RAVLTs_EscoreZ.xlsx")

library(tibble)
library(readxl)
library(dplyr)
library(gtExtras)

Carregando pacotes exigidos: gt

library(ggplot2)
library(plotly)

Attaching package: ‘plotly’

The following object is masked from ‘package:ggplot2’:

    last_plot

The following object is masked from ‘package:stats’:

    filter

The following object is masked from ‘package:graphics’:

    layout

library(viridis)

Carregando pacotes exigidos: viridisLite

library(hrbrthemes)


#setwd("C:/Users/felip/Desktop/R/3_analise")

getwd()

[1] "C:/Users/felip/Desktop/R/4_analise_"

######################################  Bubble Plots BPAs Zscore  ###############################

data <- readxl::read_xlsx ("BPAs_EscoreZ.xlsx", sheet = 1)

summary(data)

    ID...1               AGE           GROUP            EDU_LEVEL          LIMIT_AGE         BPA_CONC_POINTS
 Length:129         Min.   :20.00   Length:129         Length:129         Length:129         Min.   : 44.0  
 Class :character   1st Qu.:26.00   Class :character   Class :character   Class :character   1st Qu.: 80.0  
 Mode  :character   Median :32.00   Mode  :character   Mode  :character   Mode  :character   Median : 92.0  
                    Mean   :32.94                                                            Mean   : 92.2  
                    3rd Qu.:39.00                                                            3rd Qu.:106.0  
                    Max.   :50.00                                                            Max.   :120.0  
 BPA_CONC_EscoreZ     ID...8          BPA_DIVID_POINTS BPA_DIVID_EscoreZ   ID...11          BPA_ALTERN_POINTS
 Min.   :-2.0037   Length:129         Min.   : 26.00   Min.   :-1.8505   Length:129         Min.   : 50.00   
 1st Qu.:-0.2828   Class :character   1st Qu.: 71.00   1st Qu.:-0.1295   Class :character   1st Qu.: 87.00   
 Median : 0.3186   Mode  :character   Median : 80.00   Median : 0.2789   Mode  :character   Median : 99.00   
 Mean   : 0.3149                      Mean   : 80.22   Mean   : 0.3289                      Mean   : 97.36   
 3rd Qu.: 0.9096                      3rd Qu.: 93.00   3rd Qu.: 0.8522                      3rd Qu.:110.00   
 Max.   : 1.7190                      Max.   :116.00   Max.   : 1.8387                      Max.   :120.00   
 BPA_ALTERN_EscoreZ   ID...14            BPA_TOTAL     BPA_TOTAL_EscoreZ  
 Min.   :-1.59295   Length:129         Min.   :163.0   Min.   :-1.514929  
 1st Qu.: 0.06924   Class :character   1st Qu.:243.0   1st Qu.: 0.003583  
 Median : 0.67311   Mode  :character   Median :271.0   Median : 0.525092  
 Mean   : 0.59148                      Mean   :269.8   Mean   : 0.484156  
 3rd Qu.: 1.20840                      3rd Qu.:297.0   3rd Qu.: 1.003027  
 Max.   : 1.83333                      Max.   :350.0   Max.   : 2.103995  

colnames(data)

 [1] "ID...1"             "AGE"                "GROUP"              "EDU_LEVEL"          "LIMIT_AGE"         
 [6] "BPA_CONC_POINTS"    "BPA_CONC_EscoreZ"   "ID...8"             "BPA_DIVID_POINTS"   "BPA_DIVID_EscoreZ" 
[11] "ID...11"            "BPA_ALTERN_POINTS"  "BPA_ALTERN_EscoreZ" "ID...14"            "BPA_TOTAL"         
[16] "BPA_TOTAL_EscoreZ" 

data <- data %>% rename(ID = ID...1) %>% select(-ID...8,-ID...11,-ID...14)
  
                                        # Filtrando dados BPAs

p1 <- data %>%  select(ID,EDU_LEVEL ,GROUP ,EDU_LEVEL , AGE, BPA_CONC_POINTS , BPA_CONC_EscoreZ  )

p2 <- data %>%  select(ID,EDU_LEVEL ,GROUP ,EDU_LEVEL, AGE, BPA_DIVID_POINTS , BPA_DIVID_EscoreZ  )

p3 <- data %>%  select(ID,EDU_LEVEL ,GROUP ,EDU_LEVEL ,AGE, BPA_ALTERN_POINTS , BPA_ALTERN_EscoreZ )

ptotal <- data %>%  select(ID,EDU_LEVEL ,GROUP ,EDU_LEVEL ,AGE, BPA_ALTERN_POINTS , BPA_ALTERN_EscoreZ )

                                                #   P1  
  

coresBPA <- c("#1a2887", "#799de4")



p1 <- data %>% 
  arrange(ID) %>% 
  mutate(text = paste("Identification: ", ID , "\nAge: ", AGE , 
                      "\nPoints: ", BPA_CONC_POINTS,
                      "\nZ-Score: ", BPA_CONC_EscoreZ, sep="")) %>%
  ggplot(aes(x = AGE, y = BPA_CONC_EscoreZ, fill= GROUP, stroke = 0,
             size = AGE, shape = EDU_LEVEL , text = text)) +
  geom_point(alpha = 0.7,position = "jitter") +
  scale_fill_manual(values = coresBPA) +
  scale_size(range = c(2, 5)) +
  scale_x_continuous(name = "Age", limits = c(10, 52), breaks = seq(10, 50, by = 10)) +
  scale_y_continuous(name = "Z Score", limits = c(-3, 3), breaks = seq(-3, 3)) +
  geom_hline(yintercept = -3:3, color = "black", alpha = 0.1) + 
  geom_hline(yintercept = 0, color = "red", alpha = 0.3, linetype = "") +
  labs(y = "Y", title = "Z Score Focused Attention", shape= "", size = "") +
  theme_classic() +
  
    theme(
      text = element_text(family = "Arial Narrow", size = 11.5),
    plot.title = element_text(size = 18, face = "bold"),
    plot.subtitle = element_text(size = 18,face = "bold"),
    strip.text = element_text(size = 12),
    plot.caption = element_text(size = 9, face = "italic"),
    axis.title = element_text(size = 15),
    legend.position = "",
    legend.text = element_text(size = 5)
    )
    
            # Gráfico interativo da bibliotexa ggplottly

pp1 <- ggplotly(p1, tooltip="text") %>%
  
  layout(legend = list(x = 0, y = 1.01,
                     title = " ",
                     bgcolor = "#ecf0f1",
                     bordercolor = "white",
                     borderwidth = 1,
                     font = list(size = 9, family = "Arial", color = "black"),
                     orientation = 50,
                     tracegroupgap = 20,
                     traceorder = "normal"
                     ))
  

pp1

                                #   P2

p2 <- data %>%
  arrange(ID) %>%
  mutate(text = paste("Identification: ", ID , "\nAge: ", AGE , 
                      "\nPoints: ", BPA_DIVID_POINTS,
                      "\nZ-Score: ", BPA_DIVID_EscoreZ, sep="")) %>%
  ggplot(aes(x = AGE, y = BPA_DIVID_EscoreZ, fill= GROUP, stroke = 0,
             size = AGE, shape = EDU_LEVEL , text = text)) +
  geom_point(alpha = 0.7, position = "jitter") +
  scale_fill_manual(values = coresBPA) +
  scale_size(range = c(2, 5)) +
  scale_x_continuous(name = "Age", limits = c(10, 52), breaks = seq(10, 50, by = 10)) +
  scale_y_continuous(name = "Z Score", limits = c(-3, 3), breaks = seq(-3, 3)) +
  geom_hline(yintercept = -3:3, color = "black", alpha = 0.1) + 
  geom_hline(yintercept = 0, color = "red", alpha = 0.3, linetype = "") +
  labs(y = "Y", title = "Z Score Divid Attention", shape= "", size = "") +
  theme_classic() +
  
    theme(
      text = element_text(family = "Arial Narrow", size = 11.5),
    plot.title = element_text(size = 18, face = "bold"),
    plot.subtitle = element_text(size = 18,face = "bold"),
    strip.text = element_text(size = 12),
    plot.caption = element_text(size = 9, face = "italic"),
    axis.title = element_text(size = 15),
    legend.position = "",
    legend.text = element_text(size = 5)
    )
    

                      # Gráfico interativo da bibliotexa ggplottly

pp2 <- ggplotly(p2, tooltip="text") %>%  
 
   layout(legend = list(x = 0, y = 1.01,
                    title = " ",
                    bgcolor = "#ecf0f1",
                    bordercolor = "white",
                    borderwidth = 1,
                    font = list(size = 9, family = "Arial", color = "black"),
                    orientation = 50,
                    tracegroupgap = 20,
                    traceorder = "normal"
                    ))
 
pp2 

                                      #   P3

p3 <- data %>% 
  mutate(text = paste("Identification: ", ID , "\nAge: ", AGE , 
                      "\nPoints: ", BPA_ALTERN_POINTS,
                      "\nZ-Score: ", BPA_ALTERN_EscoreZ, sep="")) %>%
  
  ggplot(aes(x = AGE, y = BPA_ALTERN_EscoreZ, fill= GROUP, stroke = 0,
             size = AGE, shape = EDU_LEVEL , text = text)) +
  geom_point(alpha = 0.7,position = "jitter") +
  scale_fill_manual(values = coresBPA) +
  scale_size(range = c(2, 5)) +
  scale_x_continuous(name = "Age", limits = c(10, 52), breaks = seq(10, 50, by = 10)) +
  scale_y_continuous(name = "Z Score", limits = c(-3, 3), breaks = seq(-3, 3)) +
  geom_hline(yintercept = -3:3, color = "black", alpha = 0.1) + 
  geom_hline(yintercept = 0, color = "red", alpha = 0.3, linetype = "") +
  labs(y = "Y", title = "Z Score Altern Attention", shape= "", size = "") +
  theme_classic() +
  
    theme(
      text = element_text(family = "Arial Narrow", size = 11.5),
    plot.title = element_text(size = 18, face = "bold"),
    plot.subtitle = element_text(size = 18,face = "bold"),
    strip.text = element_text(size = 12),
    plot.caption = element_text(size = 9, face = "italic"),
    axis.title = element_text(size = 15),
    legend.position = "",
    legend.text = element_text(size = 5)
    )
  

                    # Gráfico interativo da bibliotexa ggplottly

pp3 <-  ggplotly(p3, tooltip="text") %>%  
  
    layout(legend = list(x = 0, y = 1.01,
                     title = " ",
                     bgcolor = "#ecf0f1",
                     bordercolor = "white",
                     borderwidth = 1,
                     font = list(size = 9, family = "Arial", color = "black"),
                     orientation = 50,
                     tracegroupgap = 20,
                     traceorder = "normal"
                     ))


pp3

                              #BPA_TOTAL

ptotal <- data %>% 
  arrange(ID) %>% 
  mutate(text = paste("Identification: ", ID , "\nAge: ", AGE , 
                      "\nPoints: ", BPA_TOTAL,
                      "\nZ-Score: ", BPA_TOTAL_EscoreZ, sep="")) %>%
  ggplot(aes(x = AGE, y = BPA_TOTAL_EscoreZ, fill= GROUP, stroke = 0,
             size = AGE, shape = EDU_LEVEL , text = text)) +
  geom_point(alpha = 0.7,position = "jitter") +
  scale_fill_manual(values = coresBPA) +
  scale_size(range = c(2, 5)) +
  scale_x_continuous(name = "Age", limits = c(10, 52), breaks = seq(10, 50, by = 10)) +
  scale_y_continuous(name = "Z Score", limits = c(-3, 3), breaks = seq(-3, 3)) +
  geom_hline(yintercept = -3:3, color = "black", alpha = 0.1) + 
  geom_hline(yintercept = 0, color = "red", alpha = 0.3, linetype = "") +
  labs(y = "Y", title = "Z Score Total", shape= "", size = "") +
  theme_classic() +
  
    theme(
      text = element_text(family = "Arial Narrow", size = 11.5),
    plot.title = element_text(size = 18, face = "bold"),
    plot.subtitle = element_text(size = 18,face = "bold"),
    strip.text = element_text(size = 12),
    plot.caption = element_text(size = 9, face = "italic"),
    axis.title = element_text(size = 15),
    legend.position = "",
    legend.text = element_text(size = 5)
    )
    
            # Gráfico interativo da bibliotexa ggplottly

pptotal <- ggplotly(ptotal, tooltip="text") %>%
  
  layout(legend = list(x = 0, y = 1.01,
                     title = " ",
                     bgcolor = "#ecf0f1",
                     bordercolor = "white",
                     borderwidth = 1,
                     font = list(size = 9, family = "Arial", color = "black"),
                     orientation = 50,
                     tracegroupgap = 20,
                     traceorder = "normal"
                     ))
  

pptotal

######################################  Bubble Plots FDTs Zscore  ###############################

data <- readxl::read_excel("FDT_EscoreZ.xlsx")

data <- na.omit(data)

colnames(data)

 [1] "ID...1"              "AGE"                 "EDU_LEVEL"           "GROUP"              
 [5] "LIMIT_AGE"           "FDT_READING_TIME"    "FDT_READING_TIME_Z"  "ID...8"             
 [9] "FDT_COUNTING_TIME"   "FDT_COUNTING_TIME_Z" "ID...11"             "FDT_CHOOSING_TIME"  
[13] "FDT_CHOOSING_TIME_Z" "ID...14"             "FDT_CHANGING_TIME"   "FDT_CHANGING_TIME_Z"
[17] "ID...17"             "FDT_INHIBITION"      "FDT_INHIBITION_Z"    "ID...20"            
[21] "FDT_FLEXIBILITY"     "FDT_FLEXIBILITY_Z"  

data <- data %>% rename(ID = ID...1)

data

                                      #  Filtrando FDTs 



p4 <- data %>%  select(ID,EDU_LEVEL ,GROUP ,AGE, FDT_READING_TIME , FDT_READING_TIME_Z  )

p5 <- data %>%  select(ID,EDU_LEVEL ,GROUP ,AGE, FDT_COUNTING_TIME , FDT_COUNTING_TIME_Z  )

p6 <- data %>%  select(ID,EDU_LEVEL ,GROUP ,AGE, FDT_CHOOSING_TIME , FDT_CHOOSING_TIME_Z )

p7 <- data %>%  select(ID,EDU_LEVEL ,GROUP ,AGE, FDT_CHANGING_TIME , FDT_CHANGING_TIME_Z )

p8 <- data %>%  select(ID,EDU_LEVEL ,GROUP ,AGE, FDT_INHIBITION , FDT_INHIBITION_Z )

p9 <- data %>%  select(ID,EDU_LEVEL ,GROUP ,AGE, FDT_FLEXIBILITY , FDT_FLEXIBILITY_Z )

                                            #  P4


coresFDT <- c("#f6a3ab", "#1ab6ac")



p4 <- data %>% 
  arrange(ID) %>% 
  mutate(text = paste("Identification: ", ID , "\nAge: ", AGE , 
                      "\nPoints: ", FDT_READING_TIME,
                      "\nZ-Score: ", FDT_READING_TIME_Z, sep="")) %>%
  ggplot(aes(x = AGE, y = FDT_READING_TIME_Z, fill= GROUP, stroke = 0,
             size = AGE, shape = EDU_LEVEL , text = text)) +
  geom_point(alpha = 0.7,position = "jitter") +
  scale_fill_manual(values = coresFDT) +
  scale_size(range = c(2, 5)) +
  scale_x_continuous(name = "Age", limits = c(10, 52), breaks = seq(10, 50, by = 10)) +
  scale_y_continuous(name = "Z Score", limits = c(-3, 3), breaks = seq(-3, 3)) +
  geom_hline(yintercept = -3:3, color = "black", alpha = 0.1) + 
  geom_hline(yintercept = 0, color = "red", alpha = 0.3, linetype = "") +
  labs(y = "Y", title = "Z Score FDT Reading Time", shape= "", size = "") +
  theme_classic() +
  
    theme(
      text = element_text(family = "Arial Narrow", size = 11.5),
    plot.title = element_text(size = 12, face = "bold"),
    plot.subtitle = element_text(size = 12),
    strip.text = element_text(size = 12),
    plot.caption = element_text(size = 9, face = "italic"),
    axis.title = element_text(size = 10),
    legend.position = "",
    legend.text = element_text(size = 5)
    )
    

pp4 <- ggplotly(p4, tooltip="text") %>%
  
  layout(legend = list(x = 0, y = 1.01,
                     title = " ",
                     bgcolor = "#ecf0f1",
                     bordercolor = "white",
                     borderwidth = 1,
                     font = list(size = 9, family = "Arial", color = "black"),
                     orientation = 50,
                     tracegroupgap = 20,
                     traceorder = "normal"
                     ))


pp4

                                      #  P5

p5 <- data %>% 
  arrange(ID) %>% 
  mutate(text = paste("Identification: ", ID , "\nAge: ", AGE , 
                      "\nPoints: ", FDT_COUNTING_TIME,
                      "\nZ-Score: ", FDT_COUNTING_TIME_Z, sep="")) %>%
  ggplot(aes(x = AGE, y = FDT_COUNTING_TIME_Z, fill= GROUP, stroke = 0,
             size = AGE, shape = EDU_LEVEL , text = text)) +
  geom_point(alpha = 0.7,position = "jitter") +
  scale_fill_manual(values = coresFDT) +
  scale_size(range = c(2, 5)) +
  scale_x_continuous(name = "Age", limits = c(10, 52), breaks = seq(10, 50, by = 10)) +
  scale_y_continuous(name = "Z Score", limits = c(-3, 3), breaks = seq(-3, 3)) +
  geom_hline(yintercept = -3:3, color = "black", alpha = 0.1) + 
  geom_hline(yintercept = 0, color = "red", alpha = 0.3, linetype = "") +
  labs(y = "Y", title = "Z Score FDT Counting Time", shape= "", size = "") +
  theme_classic() +
  
    theme(
      text = element_text(family = "Arial Narrow", size = 11.5),
    plot.title = element_text(size = 12, face = "bold"),
    plot.subtitle = element_text(size = 12),
    strip.text = element_text(size = 12),
    plot.caption = element_text(size = 9, face = "italic"),
    axis.title = element_text(size = 10),
    legend.position = "",
    legend.text = element_text(size = 5)
    )
    

pp5 <- ggplotly(p5, tooltip="text") %>%
  
  layout(legend = list(x = 0, y = 1.01,
                     title = " ",
                     bgcolor = "#ecf0f1",
                     bordercolor = "white",
                     borderwidth = 1,
                     font = list(size = 9, family = "Arial", color = "black"),
                     orientation = 50,
                     tracegroupgap = 20,
                     traceorder = "normal"
                     ))


pp5

                                      #  P6


p6 <- data %>% 
  arrange(ID) %>% 
  mutate(text = paste("Identification: ", ID , "\nAge: ", AGE , 
                      "\nPoints: ", FDT_CHOOSING_TIME,
                      "\nZ-Score: ", FDT_CHOOSING_TIME_Z, sep="")) %>%
  ggplot(aes(x = AGE, y = FDT_CHOOSING_TIME_Z, fill= GROUP, stroke = 0,
             size = AGE, shape = EDU_LEVEL , text = text)) +
  geom_point(alpha = 0.7,position = "jitter") +
  scale_fill_manual(values = coresFDT) +
  scale_size(range = c(2, 5)) +
  scale_x_continuous(name = "Age", limits = c(10, 52), breaks = seq(10, 50, by = 10)) +
  scale_y_continuous(name = "Z Score", limits = c(-3, 3), breaks = seq(-3, 3)) +
  geom_hline(yintercept = -3:3, color = "black", alpha = 0.1) + 
  geom_hline(yintercept = 0, color = "red", alpha = 0.3, linetype = "") +
  labs(y = "Y", title = "Z Score FDT Chossing Time", shape= "", size = "") +
  theme_classic() +
  
    theme(
      text = element_text(family = "Arial Narrow", size = 11.5),
    plot.title = element_text(size = 12, face = "bold"),
    plot.subtitle = element_text(size = 12),
    strip.text = element_text(size = 12),
    plot.caption = element_text(size = 9, face = "italic"),
    axis.title = element_text(size = 10),
    legend.position = "",
    legend.text = element_text(size = 5)
    )
    

pp6 <- ggplotly(p6, tooltip="text") %>%
  
  layout(legend = list(x = 0, y = 1.01,
                     title = " ",
                     bgcolor = "#ecf0f1",
                     bordercolor = "white",
                     borderwidth = 1,
                     font = list(size = 9, family = "Arial", color = "black"),
                     orientation = 50,
                     tracegroupgap = 20,
                     traceorder = "normal"
                     ))


pp6

                                      # P7


p7<- data %>% 
  arrange(ID) %>% 
  mutate(text = paste("Identification: ", ID , "\nAge: ", AGE , 
                      "\nPoints: ", FDT_CHANGING_TIME,
                      "\nZ-Score: ", FDT_CHANGING_TIME_Z, sep="")) %>%
  ggplot(aes(x = AGE, y = FDT_CHANGING_TIME_Z, fill= GROUP, stroke = 0,
             size = AGE, shape = EDU_LEVEL , text = text)) +
  geom_point(alpha = 0.7,position = "jitter") +
  scale_fill_manual(values = coresFDT) +
  scale_size(range = c(2, 5)) +
  scale_x_continuous(name = "Age", limits = c(10, 52), breaks = seq(10, 50, by = 10)) +
  scale_y_continuous(name = "Z Score", limits = c(-3, 3), breaks = seq(-3, 3)) +
  geom_hline(yintercept = -3:3, color = "black", alpha = 0.1) + 
  geom_hline(yintercept = 0, color = "red", alpha = 0.3, linetype = "") +
  labs(y = "Y", title = "Z Score FDT Changing Time", shape= "", size = "") +
  theme_classic() +
  
    theme(
      text = element_text(family = "Arial Narrow", size = 11.5),
    plot.title = element_text(size = 12, face = "bold"),
    plot.subtitle = element_text(size = 12),
    strip.text = element_text(size = 12),
    plot.caption = element_text(size = 9, face = "italic"),
    axis.title = element_text(size = 10),
    legend.position = "",
    legend.text = element_text(size = 5)
    )
    

pp7 <- ggplotly(p7, tooltip="text") %>%
  
  layout(legend = list(x = 0, y = 1.01,
                     title = " ",
                     bgcolor = "#ecf0f1",
                     bordercolor = "white",
                     borderwidth = 1,
                     font = list(size = 9, family = "Arial", color = "black"),
                     orientation = 50,
                     tracegroupgap = 20,
                     traceorder = "normal"
                     ))


pp7

                                      # P8


p8<- data %>% 
  arrange(ID) %>% 
  mutate(text = paste("Identification: ", ID , "\nAge: ", AGE , 
                      "\nPoints: ", FDT_INHIBITION,
                      "\nZ-Score: ", FDT_INHIBITION_Z, sep="")) %>%
  ggplot(aes(x = AGE, y = FDT_INHIBITION_Z, fill= GROUP, stroke = 0,
             size = AGE, shape = EDU_LEVEL , text = text)) +
  geom_point(alpha = 0.7,position = "jitter") +
  scale_fill_manual(values = coresFDT) +
  scale_size(range = c(2, 5)) +
  scale_x_continuous(name = "Age", limits = c(10, 52), breaks = seq(10, 50, by = 10)) +
  scale_y_continuous(name = "Z Score", limits = c(-3, 3), breaks = seq(-3, 3)) +
  geom_hline(yintercept = -3:3, color = "black", alpha = 0.1) + 
  geom_hline(yintercept = 0, color = "red", alpha = 0.3, linetype = "") +
  labs(y = "Y", title = "Z Score FDT Inbition", shape= "", size = "") +
  theme_classic() +
  
    theme(
      text = element_text(family = "Arial Narrow", size = 11.5),
    plot.title = element_text(size = 12, face = "bold"),
    plot.subtitle = element_text(size = 12),
    strip.text = element_text(size = 12),
    plot.caption = element_text(size = 9, face = "italic"),
    axis.title = element_text(size = 10),
    legend.position = "",
    legend.text = element_text(size = 5)
    )

pp8 <- ggplotly(p8, tooltip="text") %>%
  
  layout(legend = list(x = 0, y = 1.01,
                     title = " ",
                     bgcolor = "#ecf0f1",
                     bordercolor = "white",
                     borderwidth = 1,
                     font = list(size = 9, family = "Arial", color = "black"),
                     orientation = 50,
                     tracegroupgap = 20,
                     traceorder = "normal"
                     ))


pp8

                                    #   P9

p9<- data %>% 
  arrange(ID) %>% 
  mutate(text = paste("Identification: ", ID , "\nAge: ", AGE , 
                      "\nPoints: ", FDT_FLEXIBILITY,
                      "\nZ-Score: ", FDT_FLEXIBILITY_Z, sep="")) %>%
  ggplot(aes(x = AGE, y = FDT_FLEXIBILITY_Z, fill= GROUP, stroke = 0,
             size = AGE, shape = EDU_LEVEL , text = text)) +
  geom_point(alpha = 0.7,position = "jitter") +
  scale_fill_manual(values = coresFDT) +
  scale_size(range = c(2, 5)) +
  scale_x_continuous(name = "Age", limits = c(10, 52), breaks = seq(10, 50, by = 10)) +
  scale_y_continuous(name = "Z Score", limits = c(-3, 3), breaks = seq(-3, 3)) +
  geom_hline(yintercept = -3:3, color = "black", alpha = 0.1) + 
  geom_hline(yintercept = 0, color = "red", alpha = 0.3, linetype = "") +
  labs(y = "Y", title = "Z Score FDT Flexibility", shape= "", size = "") +
  theme_classic() +
  
    theme(
      text = element_text(family = "Arial Narrow", size = 11.5),
    plot.title = element_text(size = 12, face = "bold"),
    plot.subtitle = element_text(size = 12),
    strip.text = element_text(size = 12),
    plot.caption = element_text(size = 9, face = "italic"),
    axis.title = element_text(size = 10),
    legend.position = "",
    legend.text = element_text(size = 5)
    )
    

pp9 <- ggplotly(p9, tooltip="text") %>%
  
  layout(legend = list(x = 0, y = 1.01,
                     title = " ",
                     bgcolor = "#ecf0f1",
                     bordercolor = "white",
                     borderwidth = 1,
                     font = list(size = 9, family = "Arial", color = "black"),
                     orientation = 50,
                     tracegroupgap = 20,
                     traceorder = "normal"
                     ))


pp9

######################################  Bubble Plots RAVLTs Zscore  ###############################


data <- readxl::read_xlsx ("RAVLTs_EscoreZ.xlsx")

data

data <- data %>% dplyr::rename(ID = ID...1)

                                        # Filtrando RAVLTs 



p10 <- data %>%  select(ID,EDU_LEVEL ,GROUP ,AGE, RAVLT_A1 , RAVLT_A1_Z  )

p11 <- data %>%  select(ID,EDU_LEVEL ,GROUP ,AGE, RAVLT_A2 , RAVLT_A2_Z  )

p12 <- data %>%  select(ID,EDU_LEVEL ,GROUP ,AGE, RAVLT_A3 , RAVLT_A3_Z )

p13 <- data %>%  select(ID,EDU_LEVEL ,GROUP ,AGE, RAVLT_A4 , RAVLT_A4_Z )

p14 <- data %>%  select(ID,EDU_LEVEL ,GROUP ,AGE, RAVLT_A5 , RAVLT_A5_Z )

p15 <- data %>%  select(ID,EDU_LEVEL ,GROUP ,AGE, RAVLT_B1 , RAVLT_B1_Z )

p16 <- data %>%  select(ID,EDU_LEVEL ,GROUP ,AGE, RAVLT_A6 , RAVLT_A6_Z )

p17 <- data %>%  select(ID,EDU_LEVEL ,GROUP ,AGE, RAVLT_A7 , RAVLT_A7_Z )

p18 <- data %>%  select(ID,EDU_LEVEL ,GROUP ,AGE, RAVLT_TOTALSCORE , RAVLT_TOTALSCORE_Z )

p19 <- data %>%  select(ID,EDU_LEVEL ,GROUP ,AGE, RAVLT_REC , RAVLT_REC_Z )

p20 <- data %>%  select(ID,EDU_LEVEL ,GROUP ,AGE, RAVLT_RETENTION , RAVLT_RETENTION_Z )

p21 <- data %>%  select(ID,EDU_LEVEL ,GROUP ,AGE, RAVLT_PROAT_INTERFERENCE , RAVLT_PROAT_INTERFERENCE_Z )

p22 <- data %>%  select(ID,EDU_LEVEL ,GROUP ,AGE, RAVLT_RETRO_INTERFERENCE , RAVLT_RETRO_INTERFERENCE_Z )

                                      # P10


coresRAVLT<- c("#7f1c2b", "#9c9ce9")



p10 <- data %>% 
  arrange(ID) %>% 
  mutate(text = paste("Identification: ", ID , "\nAge: ", AGE , 
                      "\nPoints: ", RAVLT_A1,
                      "\nZ-Score: ", RAVLT_A1_Z, sep="")) %>%
  ggplot(aes(x = AGE, y = RAVLT_A1_Z, fill= GROUP, stroke = 0,
             size = AGE, shape = EDU_LEVEL , text = text)) +
  geom_point(alpha = 0.7,position = "jitter") +
  scale_fill_manual(values = coresRAVLT) +
  scale_size(range = c(2, 5)) +
  scale_x_continuous(name = "Age", limits = c(10, 52), breaks = seq(10, 50, by = 10)) +
  scale_y_continuous(name = "Z Score", limits = c(-3, 3), breaks = seq(-3, 3)) +
  geom_hline(yintercept = -3:3, color = "black", alpha = 0.1) + 
  geom_hline(yintercept = 0, color = "red", alpha = 0.3, linetype = "") +
  labs(y = "Y", title = "Z Score RAVLT A1", shape= "", size = "") +
  theme_classic() +
  
    theme(
      text = element_text(family = "Arial Narrow", size = 11.5),
    plot.title = element_text(size = 12, face = "bold"),
    plot.subtitle = element_text(size = 12),
    strip.text = element_text(size = 12),
    plot.caption = element_text(size = 9, face = "italic"),
    axis.title = element_text(size = 10),
    legend.position = "",
    legend.text = element_text(size = 5)
    )
    


pp10 <- ggplotly(p10, tooltip="text") %>%  
  
    layout(legend = list(x = 0, y = 1.01,
                     title = " ",
                     bgcolor = "#ecf0f1",
                     bordercolor = "white",
                     borderwidth = 1,
                     font = list(size = 9, family = "Arial", color = "black"),
                     orientation = 50,
                     tracegroupgap = 20,
                     traceorder = "normal"
                     ))

pp10

                                    # P11


p11 <- data %>% 
  arrange(ID) %>% 
  mutate(text = paste("Identification: ", ID , "\nAge: ", AGE , 
                      "\nPoints: ", RAVLT_A2,
                      "\nZ-Score: ", RAVLT_A2_Z, sep="")) %>%
  ggplot(aes(x = AGE, y = RAVLT_A2_Z, fill= GROUP, stroke = 0,
             size = AGE, shape = EDU_LEVEL , text = text)) +
  geom_point(alpha = 0.7,position = "jitter") +
  scale_fill_manual(values = coresRAVLT) +
  scale_size(range = c(2, 5)) +
  scale_x_continuous(name = "Age", limits = c(10, 52), breaks = seq(10, 50, by = 10)) +
  scale_y_continuous(name = "Z Score", limits = c(-3, 3), breaks = seq(-3, 3)) +
  geom_hline(yintercept = -3:3, color = "black", alpha = 0.1) + 
  geom_hline(yintercept = 0, color = "red", alpha = 0.3, linetype = "") +
  labs(y = "Y", title = "Z Score RAVLT A2", shape= "", size = "") +
  theme_classic() +
  
    theme(
      text = element_text(family = "Arial Narrow", size = 11.5),
    plot.title = element_text(size = 12, face = "bold"),
    plot.subtitle = element_text(size = 12),
    strip.text = element_text(size = 12),
    plot.caption = element_text(size = 9, face = "italic"),
    axis.title = element_text(size = 10),
    legend.position = "",
    legend.text = element_text(size = 5)
    )
    

pp11 <- ggplotly(p11, tooltip="text") %>%  
  
    layout(legend = list(x = 0, y = 1.01,
                     title = " ",
                     bgcolor = "#ecf0f1",
                     bordercolor = "white",
                     borderwidth = 1,
                     font = list(size = 9, family = "Arial", color = "black"),
                     orientation = 50,
                     tracegroupgap = 20,
                     traceorder = "normal"
                     ))

pp11

                            # P12


p12 <- data %>% 
  arrange(ID) %>% 
  mutate(text = paste("Identification: ", ID , "\nAge: ", AGE , 
                      "\nPoints: ", RAVLT_A3,
                      "\nZ-Score: ", RAVLT_A3_Z, sep="")) %>%
  ggplot(aes(x = AGE, y = RAVLT_A3_Z, fill= GROUP, stroke = 0,
             size = AGE, shape = EDU_LEVEL , text = text)) +
  geom_point(alpha = 0.7,position = "jitter") +
  scale_fill_manual(values = coresRAVLT) +
  scale_size(range = c(2, 5)) +
  scale_x_continuous(name = "Age", limits = c(10, 52), breaks = seq(10, 50, by = 10)) +
  scale_y_continuous(name = "Z Score", limits = c(-3, 3), breaks = seq(-3, 3)) +
  geom_hline(yintercept = -3:3, color = "black", alpha = 0.1) + 
  geom_hline(yintercept = 0, color = "red", alpha = 0.3, linetype = "") +
  labs(y = "Y", title = "Z Score RAVLT A3", shape= "", size = "") +
  theme_classic() +
  
    theme(
      text = element_text(family = "Arial Narrow", size = 11.5),
    plot.title = element_text(size = 12, face = "bold"),
    plot.subtitle = element_text(size = 12),
    strip.text = element_text(size = 12),
    plot.caption = element_text(size = 9, face = "italic"),
    axis.title = element_text(size = 10),
    legend.position = "",
    legend.text = element_text(size = 5)
    )
    

pp12 <- ggplotly(p12, tooltip="text") %>%  
  
    layout(legend = list(x = 0, y = 1.01,
                     title = " ",
                     bgcolor = "#ecf0f1",
                     bordercolor = "white",
                     borderwidth = 1,
                     font = list(size = 9, family = "Arial", color = "black"),
                     orientation = 50,
                     tracegroupgap = 20,
                     traceorder = "normal"
                     ))

pp12

                                # P13


p13 <- data %>% 
  arrange(ID) %>% 
  mutate(text = paste("Identification: ", ID , "\nAge: ", AGE , 
                      "\nPoints: ", RAVLT_A4,
                      "\nZ-Score: ", RAVLT_A4_Z, sep="")) %>%
  ggplot(aes(x = AGE, y = RAVLT_A4_Z, fill= GROUP, stroke = 0,
             size = AGE, shape = EDU_LEVEL , text = text)) +
  geom_point(alpha = 0.7,position = "jitter") +
  scale_fill_manual(values = coresRAVLT) +
  scale_size(range = c(2, 5)) +
  scale_x_continuous(name = "Age", limits = c(10, 52), breaks = seq(10, 50, by = 10)) +
  scale_y_continuous(name = "Z Score", limits = c(-3, 3), breaks = seq(-3, 3)) +
  geom_hline(yintercept = -3:3, color = "black", alpha = 0.1) + 
  geom_hline(yintercept = 0, color = "red", alpha = 0.3, linetype = "") +
  labs(y = "Y", title = "Z Score RAVLT A4", shape= "", size = "") +
  theme_classic() +
  
    theme(
      text = element_text(family = "Arial Narrow", size = 11.5),
    plot.title = element_text(size = 12, face = "bold"),
    plot.subtitle = element_text(size = 12),
    strip.text = element_text(size = 12),
    plot.caption = element_text(size = 9, face = "italic"),
    axis.title = element_text(size = 10),
    legend.position = "",
    legend.text = element_text(size = 5)
    )


pp13 <- ggplotly(p13, tooltip="text") %>%  
  
    layout(legend = list(x = 0, y = 1.01,
                     title = " ",
                     bgcolor = "#ecf0f1",
                     bordercolor = "white",
                     borderwidth = 1,
                     font = list(size = 9, family = "Arial", color = "black"),
                     orientation = 50,
                     tracegroupgap = 20,
                     traceorder = "normal"
                     ))

pp13

                                  #  P14


p14 <- data %>% 
  arrange(ID) %>% 
  mutate(text = paste("Identification: ", ID , "\nAge: ", AGE , 
                      "\nPoints: ", RAVLT_A5,
                      "\nZ-Score: ", RAVLT_A5_Z, sep="")) %>%
  ggplot(aes(x = AGE, y = RAVLT_A5_Z, fill= GROUP, stroke = 0,
             size = AGE, shape = EDU_LEVEL , text = text)) +
  geom_point(alpha = 0.7,position = "jitter") +
  scale_fill_manual(values = coresRAVLT) +
  scale_size(range = c(2, 5)) +
  scale_x_continuous(name = "Age", limits = c(10, 52), breaks = seq(10, 50, by = 10)) +
  scale_y_continuous(name = "Z Score", limits = c(-3, 3), breaks = seq(-3, 3)) +
  geom_hline(yintercept = -3:3, color = "black", alpha = 0.1) + 
  geom_hline(yintercept = 0, color = "red", alpha = 0.3, linetype = "") +
  labs(y = "Y", title = "Z Score RAVLT A4", shape= "", size = "") +
  theme_classic() +
  
    theme(
      text = element_text(family = "Arial Narrow", size = 11.5),
    plot.title = element_text(size = 12, face = "bold"),
    plot.subtitle = element_text(size = 12),
    strip.text = element_text(size = 12),
    plot.caption = element_text(size = 9, face = "italic"),
    axis.title = element_text(size = 10),
    legend.position = "",
    legend.text = element_text(size = 5)
    )
    

pp14 <- ggplotly(p14, tooltip="text") %>%  
  
    layout(legend = list(x = 0, y = 1.01,
                     title = " ",
                     bgcolor = "#ecf0f1",
                     bordercolor = "white",
                     borderwidth = 1,
                     font = list(size = 9, family = "Arial", color = "black"),
                     orientation = 50,
                     tracegroupgap = 20,
                     traceorder = "normal"
                     ))

pp14

                                # P15


p15 <- data %>% 
  arrange(ID) %>% 
  mutate(text = paste("Identification: ", ID , "\nAge: ", AGE , 
                      "\nPoints: ", RAVLT_B1,
                      "\nZ-Score: ", RAVLT_B1_Z, sep="")) %>%
  ggplot(aes(x = AGE, y = RAVLT_B1_Z, fill= GROUP, stroke = 0,
             size = AGE, shape = EDU_LEVEL , text = text)) +
  geom_point(alpha = 0.7,position = "jitter") +
  scale_fill_manual(values = coresRAVLT) +
  scale_size(range = c(2, 5)) +
  scale_x_continuous(name = "Age", limits = c(10, 52), breaks = seq(10, 50, by = 10)) +
  scale_y_continuous(name = "Z Score", limits = c(-3, 3), breaks = seq(-3, 3)) +
  geom_hline(yintercept = -3:3, color = "black", alpha = 0.1) + 
  geom_hline(yintercept = 0, color = "red", alpha = 0.3, linetype = "") +
  labs(y = "Y", title = "Z Score RAVLT B1", shape= "", size = "") +
  theme_classic() +
  
    theme(
      text = element_text(family = "Arial Narrow", size = 11.5),
    plot.title = element_text(size = 12, face = "bold"),
    plot.subtitle = element_text(size = 12),
    strip.text = element_text(size = 12),
    plot.caption = element_text(size = 9, face = "italic"),
    axis.title = element_text(size = 10),
    legend.position = "",
    legend.text = element_text(size = 5)
    )
    

pp15 <- ggplotly(p15, tooltip="text") %>%  
  
    layout(legend = list(x = 0, y = 1.01,
                     title = " ",
                     bgcolor = "#ecf0f1",
                     bordercolor = "white",
                     borderwidth = 1,
                     font = list(size = 9, family = "Arial", color = "black"),
                     orientation = 50,
                     tracegroupgap = 20,
                     traceorder = "normal"
                     ))

pp15

                              #  P16


p16 <- data %>% 
  arrange(ID) %>% 
  mutate(text = paste("Identification: ", ID , "\nAge: ", AGE , 
                      "\nPoints: ", RAVLT_A6,
                      "\nZ-Score: ", RAVLT_A6_Z, sep="")) %>%
  ggplot(aes(x = AGE, y = RAVLT_A6_Z, fill= GROUP, stroke = 0,
             size = AGE, shape = EDU_LEVEL , text = text)) +
  geom_point(alpha = 0.7,position = "jitter") +
  scale_fill_manual(values = coresRAVLT) +
  scale_size(range = c(2, 5)) +
  scale_x_continuous(name = "Age", limits = c(10, 52), breaks = seq(10, 50, by = 10)) +
  scale_y_continuous(name = "Z Score", limits = c(-3, 3), breaks = seq(-3, 3)) +
  geom_hline(yintercept = -3:3, color = "black", alpha = 0.1) + 
  geom_hline(yintercept = 0, color = "red", alpha = 0.3, linetype = "") +
  labs(y = "Y", title = "Z Score RAVLT A6", shape= "", size = "") +
  theme_classic() +
  
    theme(
      text = element_text(family = "Arial Narrow", size = 11.5),
    plot.title = element_text(size = 12, face = "bold"),
    plot.subtitle = element_text(size = 12),
    strip.text = element_text(size = 12),
    plot.caption = element_text(size = 9, face = "italic"),
    axis.title = element_text(size = 10),
    legend.position = "",
    legend.text = element_text(size = 5)
    )
    

pp16 <- ggplotly(p16, tooltip="text") %>%  
  
    layout(legend = list(x = 0, y = 1.01,
                     title = " ",
                     bgcolor = "#ecf0f1",
                     bordercolor = "white",
                     borderwidth = 1,
                     font = list(size = 9, family = "Arial", color = "black"),
                     orientation = 50,
                     tracegroupgap = 20,
                     traceorder = "normal"
                     ))


pp16

                                  #  P17

p17 <- data %>% 
  arrange(ID) %>% 
  mutate(text = paste("Identification: ", ID , "\nAge: ", AGE , 
                      "\nPoints: ", RAVLT_A7,
                      "\nZ-Score: ", RAVLT_A7_Z, sep="")) %>%
  ggplot(aes(x = AGE, y = RAVLT_A7_Z, fill= GROUP, stroke = 0,
             size = AGE, shape = EDU_LEVEL , text = text)) +
  geom_point(alpha = 0.7,position = "jitter") +
  scale_fill_manual(values = coresRAVLT) +
  scale_size(range = c(2, 5)) +
  scale_x_continuous(name = "Age", limits = c(10, 52), breaks = seq(10, 50, by = 10)) +
  scale_y_continuous(name = "Z Score", limits = c(-3, 3), breaks = seq(-3, 3)) +
  geom_hline(yintercept = -3:3, color = "black", alpha = 0.1) + 
  geom_hline(yintercept = 0, color = "red", alpha = 0.3, linetype = "") +
  labs(y = "Y", title = "Z Score RAVLT A7", shape= "", size = "") +
  theme_classic() +
  
    theme(
      text = element_text(family = "Arial Narrow", size = 11.5),
    plot.title = element_text(size = 12, face = "bold"),
    plot.subtitle = element_text(size = 12),
    strip.text = element_text(size = 12),
    plot.caption = element_text(size = 9, face = "italic"),
    axis.title = element_text(size = 10),
    legend.position = "",
    legend.text = element_text(size = 5)
    )
    

pp17 <- ggplotly(p17, tooltip="text") %>%  
  
    layout(legend = list(x = 0, y = 1.01,
                     title = " ",
                     bgcolor = "#ecf0f1",
                     bordercolor = "white",
                     borderwidth = 1,
                     font = list(size = 9, family = "Arial", color = "black"),
                     orientation = 50,
                     tracegroupgap = 20,
                     traceorder = "normal"
                     ))

pp17

                                      # P18

p18 <- data %>% 
  arrange(ID) %>% 
  mutate(text = paste("Identification: ", ID , "\nAge: ", AGE , 
                      "\nPoints: ", RAVLT_TOTALSCORE,
                      "\nZ-Score: ", RAVLT_TOTALSCORE_Z, sep="")) %>%
  ggplot(aes(x = AGE, y = RAVLT_TOTALSCORE_Z, fill= GROUP, stroke = 0,
             size = AGE, shape = EDU_LEVEL , text = text)) +
  geom_point(alpha = 0.7,position = "jitter") +
  scale_fill_manual(values = coresRAVLT) +
  scale_size(range = c(2, 5)) +
  scale_x_continuous(name = "Age", limits = c(10, 52), breaks = seq(10, 50, by = 10)) +
  scale_y_continuous(name = "Z Score", limits = c(-3, 3), breaks = seq(-3, 3)) +
  geom_hline(yintercept = -3:3, color = "black", alpha = 0.1) + 
  geom_hline(yintercept = 0, color = "red", alpha = 0.3, linetype = "") +
  labs(y = "Y", title = "Z Score RAVLT Total Score", shape= "", size = "") +
  theme_classic() +
  
    theme(
      text = element_text(family = "Arial Narrow", size = 11.5),
    plot.title = element_text(size = 12, face = "bold"),
    plot.subtitle = element_text(size = 12),
    strip.text = element_text(size = 12),
    plot.caption = element_text(size = 9, face = "italic"),
    axis.title = element_text(size = 10),
    legend.position = "",
    legend.text = element_text(size = 5)
    )
    

pp18 <- ggplotly(p18, tooltip="text") %>%  
  
    layout(legend = list(x = 0, y = 1.01,
                     title = " ",
                     bgcolor = "#ecf0f1",
                     bordercolor = "white",
                     borderwidth = 1,
                     font = list(size = 9, family = "Arial", color = "black"),
                     orientation = 50,
                     tracegroupgap = 20,
                     traceorder = "normal"
                     ))

pp18

                                    # P19

p19 <- data %>% 
  arrange(ID) %>% 
  mutate(text = paste("Identification: ", ID , "\nAge: ", AGE , 
                      "\nPoints: ", RAVLT_TOTALSCORE,
                      "\nZ-Score: ", RAVLT_TOTALSCORE_Z, sep="")) %>%
  ggplot(aes(x = AGE, y = RAVLT_TOTALSCORE_Z, fill= GROUP, stroke = 0,
             size = AGE, shape = EDU_LEVEL , text = text)) +
  geom_point(alpha = 0.7,position = "jitter") +
  scale_fill_manual(values = coresRAVLT) +
  scale_size(range = c(2, 5)) +
  scale_x_continuous(name = "Age", limits = c(10, 52), breaks = seq(10, 50, by = 10)) +
  scale_y_continuous(name = "Z Score", limits = c(-3, 3), breaks = seq(-3, 3)) +
  geom_hline(yintercept = -3:3, color = "black", alpha = 0.1) + 
  geom_hline(yintercept = 0, color = "red", alpha = 0.3, linetype = "") +
  labs(y = "Y", title = "Z Score RAVLT Total Score", shape= "", size = "") +
  theme_classic() +
  
    theme(
      text = element_text(family = "Arial Narrow", size = 11.5),
    plot.title = element_text(size = 12, face = "bold"),
    plot.subtitle = element_text(size = 12),
    strip.text = element_text(size = 12),
    plot.caption = element_text(size = 9, face = "italic"),
    axis.title = element_text(size = 10),
    legend.position = "",
    legend.text = element_text(size = 5)
    )
    

pp19 <- ggplotly(p19, tooltip="text") %>%  
  
    layout(legend = list(x = 0, y = 1.01,
                     title = " ",
                     bgcolor = "#ecf0f1",
                     bordercolor = "white",
                     borderwidth = 1,
                     font = list(size = 9, family = "Arial", color = "black"),
                     orientation = 50,
                     tracegroupgap = 20,
                     traceorder = "normal"
                     ))

pp19

                                  # P20

p20 <- data %>% 
  arrange(ID) %>% 
  mutate(text = paste("Identification: ", ID , "\nAge: ", AGE , 
                      "\nPoints: ", RAVLT_RETENTION,
                      "\nZ-Score: ", RAVLT_RETENTION_Z, sep="")) %>%
  ggplot(aes(x = AGE, y = RAVLT_RETENTION_Z, fill= GROUP, stroke = 0,
             size = AGE, shape = EDU_LEVEL , text = text)) +
  geom_point(alpha = 0.7,position = "jitter") +
  scale_fill_manual(values = coresRAVLT) +
  scale_size(range = c(2, 5)) +
  scale_x_continuous(name = "Age", limits = c(10, 52), breaks = seq(10, 50, by = 10)) +
  scale_y_continuous(name = "Z Score", limits = c(-3, 3), breaks = seq(-3, 3)) +
  geom_hline(yintercept = -3:3, color = "black", alpha = 0.1) + 
  geom_hline(yintercept = 0, color = "red", alpha = 0.3, linetype = "") +
  labs(y = "Y", title = "Z Score RAVLT Retention", shape= "", size = "") +
  theme_classic() +
  
    theme(
      text = element_text(family = "Arial Narrow", size = 11.5),
    plot.title = element_text(size = 12, face = "bold"),
    plot.subtitle = element_text(size = 12),
    strip.text = element_text(size = 12),
    plot.caption = element_text(size = 9, face = "italic"),
    axis.title = element_text(size = 10),
    legend.position = "",
    legend.text = element_text(size = 5)
    )
    


pp20 <- ggplotly(p20, tooltip="text") %>%  
  
    layout(legend = list(x = 0, y = 1.01,
                     title = " ",
                     bgcolor = "#ecf0f1",
                     bordercolor = "white",
                     borderwidth = 1,
                     font = list(size = 9, family = "Arial", color = "black"),
                     orientation = 50,
                     tracegroupgap = 20,
                     traceorder = "normal"
                     ))


pp20

                                    # P21

p21 <- data %>% 
  arrange(ID) %>% 
  mutate(text = paste("Identification: ", ID , "\nAge: ", AGE , 
                      "\nPoints: ", RAVLT_PROAT_INTERFERENCE,
                      "\nZ-Score: ", RAVLT_PROAT_INTERFERENCE_Z, sep="")) %>%
  ggplot(aes(x = AGE, y = RAVLT_PROAT_INTERFERENCE_Z, fill= GROUP, stroke = 0,
             size = AGE, shape = EDU_LEVEL , text = text)) +
  geom_point(alpha = 0.7,position = "jitter") +
  scale_fill_manual(values = coresRAVLT) +
  scale_size(range = c(2, 5)) +
  scale_x_continuous(name = "Age", limits = c(10, 52), breaks = seq(10, 50, by = 10)) +
  scale_y_continuous(name = "Z Score", limits = c(-3, 3), breaks = seq(-3, 3)) +
  geom_hline(yintercept = -3:3, color = "black", alpha = 0.1) + 
  geom_hline(yintercept = 0, color = "red", alpha = 0.3, linetype = "") +
  labs(y = "Y", title = "Z Score RAVLT Proative Interference", shape= "", size = "") +
  theme_classic() +
  
    theme(
      text = element_text(family = "Arial Narrow", size = 11.5),
    plot.title = element_text(size = 12, face = "bold"),
    plot.subtitle = element_text(size = 12),
    strip.text = element_text(size = 12),
    plot.caption = element_text(size = 9, face = "italic"),
    axis.title = element_text(size = 10),
    legend.position = "",
    legend.text = element_text(size = 5)
    )
    

pp21 <- ggplotly(p21, tooltip="text") %>%  
  
    layout(legend = list(x = 0, y = 1.01,
                     title = " ",
                     bgcolor = "#ecf0f1",
                     bordercolor = "white",
                     borderwidth = 1,
                     font = list(size = 9, family = "Arial", color = "black"),
                     orientation = 50,
                     tracegroupgap = 20,
                     traceorder = "normal"
                     ))

pp21

                                      #  P22

p22 <- data %>% 
  arrange(ID) %>% 
  mutate(text = paste("Identification: ", ID , "\nAge: ", AGE , 
                      "\nPoints: ", RAVLT_RETRO_INTERFERENCE,
                      "\nZ-Score: ", RAVLT_RETRO_INTERFERENCE_Z, sep="")) %>%
  ggplot(aes(x = AGE, y = RAVLT_RETRO_INTERFERENCE_Z, fill= GROUP, stroke = 0,
             size = AGE, shape = EDU_LEVEL , text = text)) +
  geom_point(alpha = 0.7,position = "jitter") +
  scale_fill_manual(values = coresRAVLT) +
  scale_size(range = c(2, 5)) +
  scale_x_continuous(name = "Age", limits = c(10, 52), breaks = seq(10, 50, by = 10)) +
  scale_y_continuous(name = "Z Score", limits = c(-3, 3), breaks = seq(-3, 3)) +
  geom_hline(yintercept = -3:3, color = "black", alpha = 0.1) + 
  geom_hline(yintercept = 0, color = "red", alpha = 0.3, linetype = "") +
  labs(y = "Y", title = "Z Score RAVLT Retroative Interference", shape= "", size = "") +
  theme_classic() +
  
    theme(
      text = element_text(family = "Arial Narrow", size = 11.5),
    plot.title = element_text(size = 12, face = "bold"),
    plot.subtitle = element_text(size = 12),
    strip.text = element_text(size = 12),
    plot.caption = element_text(size = 9, face = "italic"),
    axis.title = element_text(size = 10),
    legend.position = "",
    legend.text = element_text(size = 5)
    )
    

pp22 <- ggplotly(p22, tooltip="text") %>%  
  
    layout(legend = list(x = 0, y = 1.01,
                     title = " ",
                     bgcolor = "#ecf0f1",
                     bordercolor = "white",
                     borderwidth = 1,
                     font = list(size = 9, family = "Arial", color = "black"),
                     orientation = 50,
                     tracegroupgap = 20,
                     traceorder = "normal"
                     ))

pp22

NA
NA

#install.packages('reshape2')
library(ggplot2)
library(dplyr)
library(readxl)
library(reshape2)

getwd()

[1] "C:/Users/felip/Desktop/R/4_analise_"

df <- read_excel("RAVLTs_EscoreZ.xlsx")

colnames(df)

 [1] "ID...1"                     "AGE"                        "EDU_LEVEL"                  "GROUP"                     
 [5] "LIMIT_AGE"                  "RAVLT_A1"                   "RAVLT_A1_Z"                 "ID...8"                    
 [9] "RAVLT_A2"                   "RAVLT_A2_Z"                 "ID...11"                    "RAVLT_A3"                  
[13] "RAVLT_A3_Z"                 "ID...14"                    "RAVLT_A4"                   "RAVLT_A4_Z"                
[17] "ID...17"                    "RAVLT_A5"                   "RAVLT_A5_Z"                 "ID...20"                   
[21] "RAVLT_B1"                   "RAVLT_B1_Z"                 "ID...23"                    "RAVLT_A6"                  
[25] "RAVLT_A6_Z"                 "ID...26"                    "RAVLT_A7"                   "RAVLT_A7_Z"                
[29] "ID...29"                    "RAVLT_REC"                  "RAVLT_REC_Z"                "ID...32"                   
[33] "RAVLT_TOTALSCORE"           "RAVLT_TOTALSCORE_Z"         "ID...35"                    "RAVLT_RETENTION"           
[37] "RAVLT_RETENTION_Z"          "ID...38"                    "RAVLT_PROAT_INTERFERENCE"   "RAVLT_PROAT_INTERFERENCE_Z"
[41] "ID...41"                    "RAVLT_RETRO_INTERFERENCE"   "RAVLT_RETRO_INTERFERENCE_Z"

#1a2887, #799de4

######################################  Curva de Crescimento  ##########################################

df.RAVLTs <- df %>% select(GROUP,AGE,RAVLT_A1,RAVLT_A2,RAVLT_A3,RAVLT_A4,RAVLT_A5)


df.melted <- melt(df.RAVLTs, id.vars = c("AGE", "GROUP"), variable.name = "Variável", value.name = "Pontuação")

cores <- c("CASE" = "#1a2887", "CONTROL" = "#799de4")

# Criar o gráfico de linhas
p <- ggplot(df.melted, aes(x = AGE, y = Pontuação, color = GROUP)) +
  geom_point(alpha=0.5, position = "jitter", size = 1.5) +
  stat_smooth( method = "lm", span = 0.8, se = F)+
  labs(title = "Gráfico de Linhas RAVLT por Grupo",
       x = "AGE",
       y = "Pontuação RAVLT",
       color = "Grupos") +
  scale_color_manual(values = cores) +
  facet_wrap(~ Variável, scales = "free_y", nrow = 1) +  # Separação por GROUP (caso e controle)
  theme_minimal()

p

`geom_smooth()` using formula = 'y ~ x'

shapiro.test(df.RAVLTs$RAVLT_A5)

    Shapiro-Wilk normality test

data:  df.RAVLTs$RAVLT_A5
W = 0.95843, p-value = 0.0005649